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Mobilizing Utility Line Inspections

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Ken Thomson's picture
Director, Utilities Solutions Aquitas Solutions

An accomplished Enterprise Asset Management (EAM) and Supply Chain professional, Ken Thomson brings over 20 years of experience in asset driven industries with special focus on Utilities. As a...

  • Member since 2021
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  • Sep 1, 2021 8:15 pm GMT
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As mobile technologies become more pervasive, never has it been easier to leverage the systems most utilities already have in place to gather valuable data from regulatory inspections to make higher value investment decisions on where to spend limited ‘capital’ maintenance dollars. One recent case, a municipal utility, that conducts on average 35,000 inspections per year wanted to enhance the quality of the data collected and leverage the information being collected. The result, line inspections went from being simple YES/NO, exception identification, to truly capturing relevant asset condition information and contributing to an asset health index by gathering and analyzing this pertinent information on each asset.

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At the heart of this data collection and analysis are two systems that most utilities have in their application portfolio: the EAM (Enterprise Asset Management) and GIS (Geographic Information System) systems. The EAM system manages the regulatory PM’s and respective due dates for each asset, generating an electronic (read paperless!) inspection when required. The ‘magic’ comes when these inspections are then presented to the field workers geographically allowing seamless selection and easy input of required data. Inspections can be scheduled or as was in this use case be opportunity work and completed during down time by the appropriate crews. With the right systems and system knowledge, configuring these systems to accommodate this does not require a heavy implementation project and can be enabled in as little as three months.

Interested in how this was accomplished? Read on. Inspection questions were evaluated so a consistent set of responses were  developed. Where appropriate, several of these became characteristic type meters; the standard set of responses were applied to each meter. For example, ‘Very Good through Very bad’ (1 through 5) this made it simple for that value to be incorporated in an algorithm. This particular algorithm was developed based upon an industry organization study that provided partner utilities access to the results.

Now, in near real time, as an inspection is completed not only does it ‘drop’ off the GIS Map as a pending item, but an asset health  index is also automatically calculated and displayed on the asset record; notifications can be sent when the condition is critical. To round it all out the powerful BI tools that are also available in most utilities can present this in dashboard type format for easy interpretation and drill through capability.

How has your utility addressed Line (feeder) inspections?

Are you leveraging your EAM and GIS systems to the fullest? Visit us on our website and reach out to find out how you can take advantage of these capabilities.

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Matt Chester's picture
Matt Chester on Sep 1, 2021

For example, ‘Very Good through Very bad’ (1 through 5) this made it simple for that value to be incorporated in an algorithm.

Was further instruction given on what made the difference between a typical, say 2 vs. 3 score? 

Ken Thomson's picture
Ken Thomson on Sep 2, 2021

Matt, the values were constant 1 through 5 (very good through very bad). However the descriptions associated were tailored to the asset class being inspected. With this the user would have a description that would differentiate between a 2 or 3

Brad Mayo's picture
Brad Mayo on Sep 22, 2021

Ken,  That is what we did in our system.  The front end were textual descriptions that related to numeric values of 1-5.  Since it is easy to give an idea, here is what we had for equipment enclosure. All metal pad mounted equipment had the same inspection point making consistency across assets. " 1 - external case shows no sign of rust or paint damage", "2  - beginning signs of paint failure, no rust", "3 -  rusting but no sign of metal weakness ", '4 – RUST. metal fatigue but no non-compliant holes in structure", "5 – HEAVY RUST metal fatigue, holes in structure”.   Condition 4 and 5 would result in work orders to repair or replace equipment.  5 was immediate since it was non-compliant and posed a safety risk.  The goal is to see equipment deteriorate slowly over time due to environmental conditions.  We found areas that used reclaimed water resulted in faster paint failures which resulted in changing equipment type and paints.

Paul Korzeniowski's picture
Paul Korzeniowski on Sep 28, 2021

Good points. Capturing information remotely is now possible whereas the technology was historically just not mature enough. One area that additional information would be helpful is clean up from problems, like natural disasters. Hurricane Ida damaged 30,000 utility poles, which is nearly as many as the combined effects of Hurricane Katrina in 2005 (17,000 poles) and Hurricane Laura in 2020, according to Entergy Louisiana or Entergy New Orleans. More information helps get individuals and companies back online and get their lives back to normal, which benefits not only the customer but also the utility. 

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